Implementation issues of a high-speed distributed multi-channel ADDA system

ABSTRACT A multi-channel ADDA controller is used in many active noise cancellation and active vibration control problems. Such a controller is able to yield good performance, however it also requires a lot of hardware on a centralized place and a lot of sensitive wiring. A practical work around for this problem would be to use a local single channel controller. However such a controller would reduce the overall system performance and may introduce instability. In this paper a system will be presented that acts as a hybrid form and combines the performance of a local feedback loop with a large multi-channel controller. To reduce the wiring and the influence of disturbances on this wiring a local analog to digital and digital to analog converter will be used. These systems will be interconnected using a high-speed serial communication system. To reduce the sample rate for the overall system, a local decimation and interpolation filter will be implemented. Further performance improvements will be realized by means of a simple local feedback system. The implementation issues concerning such a system are the subject of this paper

Alternative Mechanisms for Tn5 Transposition

Bacterial transposons are known to move to new genomic sites using either a replicative or a conservative mechanism. The behavior of transposon Tn5 is anomalous. In vitro studies indicate that it uses a conservative mechanism while in vivo results point to a replicative mechanism. To explain this anomaly, a model is presented in which the two mechanisms are not independent—as widely believed—but could represent alternate outcomes of a common transpositional pathway

The use of phylogeny to interpret cross-cultural patterns in plant use and guide medicinal plant discovery: an example from Pterocarpus (Leguminosae)

The study of traditional knowledge of medicinal plants has led to discoveries that have helped combat diseases and improve healthcare. However, the development of quantitative measures that can assist our quest for new medicinal plants has not greatly advanced in recent years. Phylogenetic tools have entered many scientific fields in the last two decades to provide explanatory power, but have been overlooked in ethnomedicinal studies. Several studies show that medicinal properties are not randomly distributed in plant phylogenies, suggesting that phylogeny shapes ethnobotanical use. Nevertheless, empirical studies that explicitly combine ethnobotanical and phylogenetic information are scarce.In this study, we borrowed tools from community ecology phylogenetics to quantify significance of phylogenetic signal in medicinal properties in plants and identify nodes on phylogenies with high bioscreening potential. To do this, we produced an ethnomedicinal review from extensive literature research and a multi-locus phylogenetic hypothesis for the pantropical genus Pterocarpus (Leguminosae: Papilionoideae). We demonstrate that species used to treat a certain conditions, such as malaria, are significantly phylogenetically clumped and we highlight nodes in the phylogeny that are significantly overabundant in species used to treat certain conditions. These cross-cultural patterns in ethnomedicinal usage in Pterocarpus are interpreted in the light of phylogenetic relationships.This study provides techniques that enable the application of phylogenies in bioscreening, but also sheds light on the processes that shape cross-cultural ethnomedicinal patterns. This community phylogenetic approach demonstrates that similar ethnobotanical uses can arise in parallel in different areas where related plants are available. With a vast amount of ethnomedicinal and phylogenetic information available, we predict that this field, after further refinement of the techniques, will expand into similar research areas, such as pest management or the search for bioactive plant-based compounds

Cancer survivors’ experiences of a community-based cancer-specific exercise programme: results of an exploratory survey

Purpose Exercise levels often decline following cancer diagnosis despite growing evidence of its benefits. Treatment side-effects, older age, lack of confidence and opportunity to exercise with others in similar circumstances influence this. Our study explored the experiences of people attending a cancer-specific community-based exercise programme (CU Fitter™). Methods A survey distributed to those attending the programme gathered demographic/clinical information, self-reported exercise levels, information provision and barriers to/benefits of exercise. Results Sixty surveys were evaluable from 65/100 returned (62% female, 68% >60yrs, 66% breast/prostate cancer). Most (68%) were receiving treatment. 68% attended classes once or twice weekly. 55% received exercise advice after diagnosis, usually from their hospital doctor/nurse. More (73%) had read about exercising, but less used the internet to source information (32%). Self-reported exercise levels were higher currently than before diagnosis (p=0.05). 48% said their primary barrier to exercising was the physical impact of cancer/treatment. Improving fitness/health (40%) and social support (16%) were the most important gains from the programme. Many (67%) had made other lifestyle changes and intented to keep (50%), or increase (30%) exercising. Conclusions This community-based cancer-specific exercise approach engaged people with cancer and showed physical, psychological, and social benefits. Implications for cancer survivors Community grown exercise initiatives bring cancer survivors together creating their own supportive environment. Combining this with instructors familiar with the population and providing an open-ended service may prove particularly motivating and beneficial. Further work is required to provide evidence for this

Translation Levels Control Multi-Spanning Membrane Protein Expression

Attempts to express eukaryotic multi-spanning membrane proteins at high-levels have been generally unsuccessful. In order to investigate the cause of this limitation and gain insight into the rate limiting processes involved, we have analyzed the effect of translation levels on the expression of several human membrane proteins in Escherichia coli (E. coli). These results demonstrate that excessive translation initiation rates of membrane proteins cause a block in protein synthesis and ultimately prevent the high-level accumulation of these proteins. Moderate translation rates allow coupling of peptide synthesis and membrane targeting, resulting in a significant increase in protein expression and accumulation over time. The current study evaluates four membrane proteins, CD20 (4-transmembrane (TM) helixes), the G-protein coupled receptors (GPCRs, 7-TMs) RA1c and EG-VEGFR1, and Patched 1 (12-TMs), and demonstrates the critical role of translation initiation rates in the targeting, insertion and folding of integral membrane proteins in the E. coli membrane

Evaluating the impact of MEDLINE filters on evidence retrieval: study protocol

<p>Abstract</p> <p>Background</p> <p>Rather than searching the entire MEDLINE database, clinicians can perform searches on a filtered set of articles where relevant information is more likely to be found. Members of our team previously developed two types of MEDLINE filters. The 'methods' filters help identify clinical research of high methodological merit. The 'content' filters help identify articles in the discipline of renal medicine. We will now test the utility of these filters for physician MEDLINE searching.</p> <p>Hypothesis</p> <p>When a physician searches MEDLINE, we hypothesize the use of filters will increase the number of relevant articles retrieved (increase 'recall,' also called sensitivity) and decrease the number of non-relevant articles retrieved (increase 'precision,' also called positive predictive value), compared to the performance of a physician's search unaided by filters.</p> <p>Methods</p> <p>We will survey a random sample of 100 nephrologists in Canada to obtain the MEDLINE search that they would first perform themselves for a focused clinical question. Each question we provide to a nephrologist will be based on the topic of a recently published, well-conducted systematic review. We will examine the performance of a physician's unaided MEDLINE search. We will then apply a total of eight filter combinations to the search (filters used in isolation or in combination). We will calculate the recall and precision of each search. The filter combinations that most improve on unaided physician searches will be identified and characterized.</p> <p>Discussion</p> <p>If these filters improve search performance, physicians will be able to search MEDLINE for renal evidence more effectively, in less time, and with less frustration. Additionally, our methodology can be used as a proof of concept for the evaluation of search filters in other disciplines.</p

Studying Language Change Using Price Equation and Pólya-urn Dynamics

Language change takes place primarily via diffusion of linguistic variants in a population of individuals. Identifying selective pressures on this process is important not only to construe and predict changes, but also to inform theories of evolutionary dynamics of socio-cultural factors. In this paper, we advocate the Price equation from evolutionary biology and the Pólya-urn dynamics from contagion studies as efficient ways to discover selective pressures. Using the Price equation to process the simulation results of a computer model that follows the Pólya-urn dynamics, we analyze theoretically a variety of factors that could affect language change, including variant prestige, transmission error, individual influence and preference, and social structure. Among these factors, variant prestige is identified as the sole selective pressure, whereas others help modulate the degree of diffusion only if variant prestige is involved. This multidisciplinary study discerns the primary and complementary roles of linguistic, individual learning, and socio-cultural factors in language change, and offers insight into empirical studies of language change

Different Pattern of Immunoglobulin Gene Usage by HIV-1 Compared to Non-HIV-1 Antibodies Derived from the Same Infected Subject

A biased usage of immunoglobulin (Ig) genes is observed in human anti-HIV-1 monoclonal antibodies (mAbs) resulting probably from compensation to reduced usage of the VH3 family genes, while the other alternative suggests that this bias usage is due to antigen requirements. If the antigen structure is responsible for the preferential usage of particular Ig genes, it may have certain implications for HIV vaccine development by the targeting of particular Ig gene-encoded B cell receptors to induce neutralizing anti-HIV-1 antibodies. To address this issue, we have produced HIV-1 specific and non-HIV-1 mAbs from an infected individual and analyzed the Ig gene usage. Green-fluorescence labeled virus-like particles (VLP) expressing HIV-1 envelope (Env) proteins of JRFL and BaL and control VLPs (without Env) were used to select single B cells for the production of 68 recombinant mAbs. Ten of these mAbs were HIV-1 Env specific with neutralizing activity against V3 and the CD4 binding site, as well as non-neutralizing mAbs to gp41. The remaining 58 mAbs were non-HIV-1 Env mAbs with undefined specificities. Analysis revealed that biased usage of Ig genes was restricted only to anti-HIV-1 but not to non-HIV-1 mAbs. The VH1 family genes were dominantly used, followed by VH3, VH4, and VH5 among anti-HIV-1 mAbs, while non-HIV-1 specific mAbs preferentially used VH3 family genes, followed by VH4, VH1 and VH5 families in a pattern identical to Abs derived from healthy individuals. This observation suggests that the biased usage of Ig genes by anti-HIV-1 mAbs is driven by structural requirements of the virus antigens rather than by compensation to any depletion of VH3 B cells due to autoreactive mechanisms, according to the gp120 superantigen hypothesis

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology